| Sumario: | A unique keynote speech by Yangqing Jia, the leader of Alibaba’s AI and Big Data organization. A revealing talk by Ion Stoica (UC Berkeley) describing some the AI projects underway at UC Berekely's renowned RISELab. A thoughtful presentation by Long Wang, VP of TenCent Cloud, illustrating what TenCent believes AI will do for the cloud. These are just three of the illuminating talks given by the many AI experts from China, the U.S., and elsewhere who gathered to speak at O'Reilly Media's Artificial Intelligence Conference Beijing June 2019. This video compilation gives you the opportunity to see all of the best presentations from AI Beijing—it contains more than 60 hours of material to review on your schedule. AI Beijing's unique focus is applied AI—bridging the gap between AI developments in research and their commercial applications in business and industry. If you want to understand how AI will change the business landscape, or are working with deep learning or AI (or plan to be)— this video compilation is for you. Highlights include: Complete video recordings from the best of AI Beijing June 2019—this video compilation contains hours of material to review at your own schedule. 55% of the presentations are in English, 42% are in Chinese, and 3% are in English and Chinese. Keynote speeches by AI thought leaders such as Maria Zhang (LinkedIn), Pete Warden (Google Brain Team), Michael James (Cerebras), Hao Zheng (PlusAI), and Tim Kraska (MIT). Tutorials in Chinese, including Intels' Zhen Zhao's exploration into the OpenVINO toolkit and Microsoft's Henry Zeng, Lu Zhang, and Xiao Zhang's introduction to automated machine learning using Python and AutoML. Tutorials in English, such as Alejandro Saucedo's (The Institute for Ethical AI & Machine Learning) practical guide to de-mystifying machine learning bias and Richard Liaw (UC Berkeley RISELab) on how to build reinforcement learning models and AI applications with Ray. "Implementing AI" sessions presented in Chinese, such as Zhenxiao Luo (Uber) on how to run big data and machine learning systems at scale; Hui Xue (Microsoft) on the latest automated machine learning advances at Microsoft Research Asia; and Guoqiong Song (Intel) and Luyang Wang (Office Depot) on how Home Depot's real-time recommendation system was built using Analytics Zoo on BigDL and Apache Spark "Implementing AI sessions" delivered in English, including Google's Kaz Sato's examination of ML operations and Kubeflow pipelines; Rak...
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